Integrating ALOS-PALSAR and ground based observations for forest biomass estimation for REDD+ in Cambodia

Abstract

Forest cover change is an important aspect of global environmental change because of rapid deforestation in tropical areas. Anthropogenic activities and natural phenomena can cause deforestation and forest degradation that adversely impacts biodiversity and ecosystem services. In 2008, the United Nations Convention on Climate Change (UNFCCC) programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) was launched to curb deforestation and forest degradation in tropical countries. The UNFCCC COP21 Paris Agreement highlighted "encouragement for Parties to implement existing frameworks for a REDD+ mechanism". For effectively implementing a REDD+ mechanism, a robust cost-effective Measurement, Reporting and Verification (MRV) system should be developed. Geospatial data has been key for the implementation of REDD+ MRV system. In this research, aboveground biomass (AGB) of forests in Cambodia was estimated using a bottom-up approach based on field estimated biomass and PALSAR backscattering (σ o) properties. The relationship between the PALSAR σ o HV and HH/HV with field-based biomass was strong with adjusted R squared (R 2 adj) = 0.66 and 0.54, respectively as compared with HH polarization. ABSTRACT KEYWORDS DOI DATES HIGHLIGHTS » PALSAR is effective in monitoring biomass and its changes without limitations of clouds » National level biomass information is useful in implementing sustainable forest management practices required for REDD+ » Empirical, remote sensing and modelling studies can be useful for generating biomass information for REDD+ MRV implementation